| Project/Area Number |
19560447
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Control engineering
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| Research Institution | Oita University |
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Principal Investigator |
MATSUO Takami Oita University, 工学部, 教授 (90181700)
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| Co-Investigator(Kenkyū-buntansha) |
HOSHINO Osamu 茨城大学, 工学部, 教授 (00303016)
SUEMITSU Haruo 大分大学, 工学部, 助教 (50162839)
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| Project Period (FY) |
2007 – 2009
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| Project Status |
Completed (Fiscal Year 2009)
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| Budget Amount *help |
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2009: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2008: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2007: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
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| Keywords | アイドリング系 / ニューロン / 振動子 / リミットサイクル / バースティング |
|---|
| Research Abstract |
In traditional artificial neural networks, the neuron behavior is described only in terms of firing rate, while most real neurons, commonly known as spiking neurons, transmit information by pulses, also called action potentials or spikes. We have presented three adaptive observers for a single neuron with the membrane potential measurement under the assumption that some of parameters in the HR neuron are known. Using the Kalman-Yakubovich lemma, we have shown the asymptotic stability of the error systems based on the standard adaptive control theory\cite{narendra}. The estimators allow us to recover the internal states and to distinguish the firing patterns with early-time dynamic behaviors.
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